Characterization of proteome-size scaling by integrative omics reveals mechanisms of proliferation control in cancer.

Almost all living cells maintain size uniformity through successive divisions. Proteins that over and underscale with size can act as rheostats, which regulate cell cycle progression. Using a multiomic strategy, we leveraged the heterogeneity of melanoma cell lines to identify peptides, transcripts, and phosphorylation events that differentially scale with cell size. Subscaling proteins are enriched in regulators of the DNA damage response and cell cycle progression, whereas super-scaling proteins included regulators of the cytoskeleton, extracellular matrix, and inflammatory response. Mathematical modeling suggested that decoupling growth and proliferative signaling may facilitate cell cycle entry over senescence in large cells when mitogenic signaling is decreased. Regression analysis reveals that up-regulation of TP53 or CDKN1A/p21CIP1 is characteristic of proliferative cancer cells with senescent-like sizes/proteomes. This study provides one of the first demonstrations of size-scaling phenomena in cancer and how morphology influences the chemistry of the cell.

Use of anthropometric measures to predict insulin resistance.

OBJECTIVE: Obesity is closely related to insulin-resistance (IR) but it is evaluated differently in the diverse definitions of the metabolic syndrome. The objective of this study was to verify the utility of different anthropometric measures to predict IR and to evaluate the best cut-off points. SUBJECTS AND METHOD: We performed a cross-sectional study of the general population aged 40 to 70 years old (n=2,143); a simple random sample of 305 non-diabetic persons was obtained. Sociodemographic data, physical examination and routine biochemical analysis with insulinemia were obtained. IR was defined by a HOMA index (Homeostasis Model Assessment) ≥2.9. To obtain the best variables to predict IR, a forward stepwise logistic regression was performed. Subsequently, a logistic equation was constructed and its predictive capacity was compared with the different anthropometric variables by the area under the ROC (receiver-operating characteristic) curve (AUC). The best cut-off points were established according to the Youden index. RESULTS: Body mass index (BMI) and the waist/hip ratio ×100 were entered into the model, but age, sex, waist, hip and body surface were not. The logistic equation found: p(RI)=1/1+exp{-[-14.295]-[0.234×IMC]-[0.07×(waist/hip×100)]} showed good adjustment, and the probability calculated on the basis of this equation showed the greatest AUC overall and in both sexes, followed in women by BMI and by waist measurement in men, but without significant differences. CONCLUSIONS: No significant differences were found between the BMI, waist or hip measurements and the logistic model to predict IR.

The concentrations of soluble vascular cell adhesion molecule-1 and lipids are independently associated with venous thromboembolism.

BACKGROUND AND OBJECTIVES: Venous thromboembolism (VTE) involves inflammation and a relation with dyslipidemia which remains controversial. The vascular cell adhesion molecule-1 (VCAM-1) is a ligand expressed by activated endothelium (and recruits leukocytes) whose soluble form (sVCAM-1) increases in atherosclerosis, severe hypertriglyceridemia or deep vein thrombosis (DVT) in acute phase. We analyzed the association between VTE (> 6 months after), sVCAM-1 and lipid concentrations. DESIGN AND METHODS: Case-control study involving 126 consecutive patients (aged 25-80 years, 49% males) and 125 controls of similar age and gender. RESULTS: The patients had a more unfavorable lipid profile than controls [higher triglycerides (p<0.001), LDLc/HDLc ratio (p<0.01) or total cholesterol (TC) (p=0.07)] and higher sVCAM-1 concentration (p<0.01) even adjusting for arterial diseases. VTE was associated with extreme values of TC, LDL-c, triglycerides (>P90) and HDL-c (P90) (OR=4.2)(p<0.0001). The sVCAM-1 values were age-related (r=0.26, p<0.001) but independent of lipid levels. Hazards ratios from five-fold to ten-fold appeared when combining the sVCAM-1 top quartile (>970 ng/mL) with TC >250 mg/dL or HDL-c <45 mg/dL (p<0.01) irrespective of thrombophilic status. Recurrent or severe VTE cases (pulmonary embolism or proximal DVT vs. distal DVT) showed higher sVCAM-1 values (p<0.05). All the associations weakened among females. In stepwise logistic regression, obesity (p<0.001), sVCAM-1 (p<0.001) and LDL-c (p=0.004) in men and sVCAM-1 (p=0.02) and triglycerides (p=0.04) in women retained their independent association. INTERPRETATION AND CONCLUSIONS: Although the exact mechanisms linking abnormal lipid and sVCAM-1 concentrations to VTE await clarification, both seem to be independently associated.

Signaling networks converge on TORC1-SREBP activity to promote endoplasmic reticulum homeostasis.

The function and capacity of the endoplasmic reticulum (ER) is determined by multiple processes ranging from the local regulation of peptide translation, translocation, and folding, to global changes in lipid composition. ER homeostasis thus requires complex interactions amongst numerous cellular components. However, describing the networks that maintain ER function during changes in cell behavior and environmental fluctuations has, to date, proven difficult. Here we perform a systems-level analysis of ER homeostasis, and find that although signaling networks that regulate ER function have a largely modular architecture, the TORC1-SREBP signaling axis is a central node that integrates signals emanating from different sub-networks. TORC1-SREBP promotes ER homeostasis by regulating phospholipid biosynthesis and driving changes in ER morphology. In particular, our network model shows TORC1-SREBP serves to integrate signals promoting growth and G1-S progression in order to maintain ER function during cell proliferation.